Summer at ViaLogy Ronald J. Perez. ViaLogy Developers of computational products for increased performance of molecular detection systems ViaAmp Gene expression.

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Summer at ViaLogy Ronald J. Perez

ViaLogy Developers of computational products for increased performance of molecular detection systems ViaAmp Gene expression amplification software designed to use active signal processing technology Differentiation of true signal from background noise

Project Showing the limitations of passive analysis Standard microarray image analysis software represented by GenePix Deliverables Processed 18 microarray images using passive analysis Classified arrays into triplicates according to dilution Given initial condition: ratio of green to red intensity is 1 Focus on array intensities as opposed to gene regulation

What did I analyze? 18 Microarrays, 340 spots on each array and since each gene is in duplicate, there are a total of 170 genes There were 6 different levels of dilution across 18 arrays Dilution StepDilution Factor Stock solutionOriginal Concentration 11:10 21:100 31: : :100000

Most Concentrated Array Most Diluted Array

GenePix Output File BlockColumnRowNameID B635 SD B532 SD Ratio of Medians (635/532) F635 Median - B635 F532 Median - B532 F635 Mean - B635 F532 Mean - B Gene 1aNC Gene 1bNC Gene 2aNC Gene 2bNC Gene 3aNC Gene 3bNC Gene 4aNC Gene 4bNC Gene 5aNC Gene 5bNC

Calculating Signal to Noise There are two ways to calculate signal to noise ratio (S/N) from a microarray spot: The first S/N definition used by Vialogy is calculated the following way: S/N (1) = F oreground Median – B ackground The second S/N definition used by the client who sent us the arrays is: S/N (2) = (F oreground Mean – B ackground )/SD of B ackground

GenePix Reproducibility If GenePix data were 100% reproducible, one would see a line with slope of 1 when plotting the S/N ratios of two independent analysis. When a scatter plot was made, some data points did not fall on a straight line. Since most data points fall on a straight line, we assumed the output data is credible and safe to continue analyzing.

Reproducibility Graph

Microarray Categorization The first approach taken to classify this set of 18 arrays into triplets was to plot the S/N ratio of all 170 genes vs. arrays. This plot will give a rough idea of the intensity pattern of these microarrays. Did GenePix do a good job analyzing these microarrays?

Gene Intensity per Array

Client Selected Groups Instead of looking at all 170 genes, our client gave us a list of 48 genes to focus on. These genes had a S/N ratio greater than 2 and where classified into the following 4 groups: Focus on C and D because they have highest S/N ratio GroupsS/N ratio Level A Level B Level C Level D>50

Analysis of Groups C and D Genes in Levels C and D were used to design a different categorization scheme. S/N ratios of Genes in Level C were summed up and the MEAN was taken separately for each array. Same was done for Level D genes. Level C and D MEANS were averaged. S/N ratios of Genes in Level C were summed up and this time the MEDIAN was taken separately for each array. Same was done for Level D genes Level C and D MEDIANS were also averaged.

Mean and Median Approach MEAN INTENSITYMEDIAN INTENSITY

Categorization Summary

Future Direction I have only told half of the story, the next steps are to: Process microarrays using ViaAmp Passive analysis vs. active analysis ViaAmp results Sensitivity and Specificity studies

Thanks Vialogy Team - Dr. David Robbins SoCalBSI Team NSF, NIH